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Many radiative transfer schemes approximate the spectral integration over ∼105 to ∼106 wavelengths with correlated k‐distributions methods that typically require only 101–102 spectral integration points (g‐points). The exact number of g‐points is then chosen as an optimal balance between computational costs and accuracy, normally assessed in terms of a number of radiative quantities. How this radiative accuracy propagates to simulation accuracy, however, is not straightforward. In this study, we therefore explore the sensitivity of cloud properties in large‐eddy simulations (LES) to the accuracy of radiative fluxes and heating rates. We first generate smaller sets of g‐points from existing k‐distributions by repeatedly combining adjacent g‐points while maintaining the highest possible accuracy on a chosen set of radiative metrics. Next, we perform three sets of LES with varying cloud—radiation coupling pathways, and therefore different requirements for the accuracy of the radiative transfer computations, to investigate how these smaller and thus less accurate k‐distributions affect simulation characteristics. The decrease in radiative accuracy with 3–4 times smaller k‐distributions results in biases in cloud properties that are relative small compared to their temporal fluctuations. These results show potential for speeding up radiative transfer computations in cloud‐resolving models by reducing the resolved spectral detail. However, more statistically converged simulations and a wider set of case studies is required to fully assess the robustness of our results. Plain Language Summary: Radiation emitted by the sun and the earth drives our weather and climate. Atmospheric models therefore need to compute how solar and thermal radiation interacts with cloud droplets, aerosols, and gas molecules. These computations can be performed very accurately by doing independent calculations for many wavelengths, but that is very time‐consuming. Here, we study to what extent the accuracy of the radiation computations affects the accuracy of simulations of the atmosphere. We find that the reduction in radiative accuracy corresponding to 3–4 times fewer representative computations results in relative small mean errors in cloud properties compared to the temporal fluctuations. In further research, we should aim to better understand whether the mean errors are small enough to represent accurate simulations. Key Points: We investigate the sensitivity of moist convection to the spectral detail of gas opticsWe perform multiple large‐eddy simulations, with progressively smaller k‐distributions, for three case studies of convective cloudsMean differences in simulated cloud properties are relatively small compared to temporal fluctuations [ABSTRACT FROM AUTHOR]

Global reanalyzes like ERA5 accurately capture atmospheric processes at spatial scales of O(10) $\mathcal{O}(10)$ km or larger. By downscaling ERA5 with large‐eddy simulation (LES), LES can provide details about processes at spatio‐temporal scales down to meters and seconds. Here, we present an open‐source Python package named the "Large‐eddy simulation and Single‐column model—Large‐Scale Dynamics," or (LS)2D in short, designed to simplify the downscaling of ERA5 with doubly‐periodic LES. A validation with observations, for several sensitivity experiments consisting of month‐long LESs over Cabauw (the Netherlands), demonstrates both its usefulness and limitations. The day‐to‐day variability in the weather is well captured by (LS)2D and LES, but the setup under‐performs in conditions with broken or near overcast clouds. As a novel application of this modeling system, we used (LS)2D to study surface solar irradiance variability, as this quantity directly links land‐surface processes, turbulent transport, and clouds, to radiation. At a horizontal resolution of 25 m, the setup reproduces satisfactorily the solar irradiance variability down to a timescale of seconds. This demonstrates that the coupled LES‐ERA5 setup is a useful tool that can provide details on the physics of turbulence and clouds, but can only improve on its host reanalysis when applied to meteorological suitable conditions. Plain Language Summary: Modern global weather models are accurate in predicting atmospheric processes at scales of around 10 km or larger, but are less good at predicting smaller scale processes, like for example, the interaction between solar radiation, individual clouds, and the resulting clouds shadows that are cast onto the land surface. High spatio‐temporal resolution research models are able to capture these smaller scale processes, but require a coupling to a weather model to account for the day‐to‐day variability in our weather. In this paper, we present a framework to couple large to small scale models, and demonstrate both the benefits and challenges of using this coupled model setup. The coupled setup excels in capturing the aforementioned high frequency interactions between small clouds and surface solar radiation. However, the chaotic nature of broken to overcast clouds is proven difficult to represent. The coupled model setup is published as open‐source code, and is therefore freely available to the research community. Key Points: We developed an open‐source Python package named (LS)2D, designed to downscale the ERA5 reanalysis with turbulence and cloud‐resolving large‐eddy simulation (LESs)One month long experiments with (LS)2D and MicroHH over the Netherlands demonstrate both the skill and limitations of the coupled setupCapturing high‐frequency interactions between clouds and surface solar irradiance requires high resolution (O $\mathcal{O}$(10) m) LES [ABSTRACT FROM AUTHOR]

We present simulations of cumulus convection over land with shortwave radiation computed by a Monte Carlo ray tracer coupled to the flow solver. Ray tracing delivers very realistic in‐cloud heating rates and global horizontal irradiance fields. The necessary performance of the ray tracer has been enabled by the raw power of graphics processing unit computing and from techniques for accelerating data lookup and ray tracer convergence. We used a case study over a grassland in the Netherlands to compare simulations with a coupled ray tracer to those with a conventional two‐stream solver, and to test ray tracer convergence. We demonstrate that the simulated cloud evolution is insensitive to the convergence of the ray tracing across a wide range of samples per pixel per spectral quadrature point. Furthermore, simulations with a coupled ray tracer produce surface irradiance patterns that resemble observations and that strongly feed back to the evolution of clouds via locally enhanced surface heat fluxes. Plain Language Summary: Clouds absorb and reflect solar radiation and create spatial patterns at the land surface of cloud shadows interspersed with sunny regions. These patterns are currently largely simplified in most weather models because radiation computations cost a lot of computer power. We have developed a fast and realistic numerical radiation model that runs on a modern computer graphics card. By doing so, we can do simulations that produce radiation patterns that closely resemble reality and study how these patterns affect clouds. This enables us to improve our understanding of the complex interactions between clouds, solar radiation, and the Earth's surface. Key Points: We present graphics processing unit‐accelerated cloud‐resolving simulations with a coupled ray tracerSimulated cloud statistics are insensitive to ray tracer convergence across a wide range of sample sizesStrong coupling between surface irradiance patterns and cloud evolution underlines need for coupled 3D radiative transfer [ABSTRACT FROM AUTHOR]

We study the combined effects of land surface conditions, atmospheric boundary layer dynamics and chemistry on the diurnal evolution of biogenic secondary organic aerosol in the atmospheric boundary layer, using a model that contains the essentials of all these components. First, we evaluate the model for a case study in Hyytiälä, Finland, and find that it is able to satisfactorily reproduce the observed dynamics and gas-phase chemistry. We show that the exchange of organic aerosol between the free troposphere and the boundary layer (entrainment) must be taken into account in order to explain the observed diurnal cycle in organic aerosol (OA) concentration. An examination of the budgets of organic aerosol and terpene concentrations show that the former is dominated by entrainment, while the latter is mainly driven by emission and chemical transformation. We systematically investigate the role of the land surface, which governs both the surface energy balance partitioning and terpene emissions, and the large-scale atmospheric process of vertical subsidence. Entrainment is especially important for the dilution of organic aerosol concentrations under conditions of dry soils and low terpene emissions. Subsidence suppresses boundary layer growth while enhancing entrainment. Therefore, it influences the relationship between organic aerosol and terpene concentrations. Our findings indicate that the diurnal evolution of secondary organic aerosols (SOA) in the boundary layer is the result of coupled effects of the land surface, dynamics of the atmospheric boundary layer, chemistry, and free troposphere conditions. This has potentially some consequences for the design of both field campaigns and large-scale modeling studies. [ABSTRACT FROM AUTHOR]

An explanatory model study is presented on semivolatile secondary inorganic aerosols on three clear days in May 2008 during the IMPACT campaign at the Cabauw tower in the Netherlands. A single column model in combination with the equilibrium aerosol model ISORROPIA is used. This model uses surface observations from IMPACT and calculates the gas-aerosol partitioning of ammonium nitrate. The calculated gas-aerosol equilibrium overestimates the gas phase fraction during daytime, and overestimates the aerosol phase fraction during night-time. This discrepancy can partly be solved when the approach of the gas-aerosol equilibrium is forced to proceed with a delay timescale of up to two hours. Although it is shown that the delay itself has a small effect, the most important effect is caused by the mixing of air from higher altitudes at which the equilibrium is shifted to the aerosol phase. Thus, vertical mixing is shown to have a significant influence on the calculated partitioning at the surface. On some occasions, the correspondence to the observed partitioning improves dramatically. Even though gas-aerosol partitioning of ammonium nitrate is not instantaneous, observations show that a different equilibrium in the upper boundary layer causes aerosol ammonium nitrate concentrations to increase with altitude. Our model calculates similar vertical gradients depending on the assumed speed of gas-aerosol equilibrium. The calculated optical properties of the aerosol show a similar behaviour. The aerosol optical properties depend on the aerosol size distribution both directly, because light scattering depends on particle size, and indirectly, because the equilibration timescale depends on the aerosol sizes. Future studies should therefore focus on a fully size-resolved treatment of the gas-aerosol partitioning. Finally, coarser-resolution models may treat the gasaerosol equilibrium of ammonium nitrate by calculating the equilibrium with a temperature and humidity sampled at a different altitude. We found that the equilibrium at an altitude of 200m (night) up to 600m (day) is representative for the partitioning of ammonium nitrate at the surface in the beginning of May 2008. [ABSTRACT FROM AUTHOR]

Interpretation of observed diurnal carbon dioxide (CO2) mixing ratios near the surface requires knowledge of the local dynamics of the planetary boundary layer. In this paper, we study the relationship between the boundary layer dynamics and the CO2 budget in convective conditions through a newly derived set of analytical equations. From these equations, we are able to quantify how uncertainties in boundary layer dynamical variables or in the morning CO2 distribution in the mixed-layer or in the free atmosphere (FA) influence the bulk CO2 mixing ratio. We find that the largest uncertainty incurred on the midday CO2 mixing ratio comes from the prescribed early morning CO2 mixing ratios in the stable boundary layer, and in the free atmosphere. Errors in these values influence CO2 mixing ratios inversely proportional to the boundary layer depth (h), just like uncertainties in the assumed initial boundary layer depth and surface CO2 flux. The influence of uncertainties in the boundary layer depth itself is one order of magnitude smaller. If we "invert" the problem and calculate CO2 surface exchange from observed or simulated CO2 mixing ratios, the sensitivities to errors in boundary layer dynamics also invert: they become linearly proportional to the boundary layer depth. We demonstrate these relations for a typical well characterized situation at the Cabauw site in The Netherlands, and conclude that knowledge of the temperature and carbon dioxide profiles of the atmosphere in the early morning are of vital importance to correctly interpret observed CO2 mixing ratios during midday. [ABSTRACT FROM AUTHOR]

Interpretation of observed diurnal carbon dioxide (CO2) mixing ratios near the surface requires knowledge of the local dynamics of the planetary boundary layer. In this paper, we quantify the relationship between the boundary layer dynamics and the CO2 budget in convective conditions through a newly derived set of analytical equations. From these equations, we are able to quantify how uncertainties in boundary layer dynamical variables or in the morning CO2 distribution in the mixed-layer or in the free atmosphere influence the bulk CO2 mixing ratio. We find that the largest uncertainty incurred on the mid-day CO2 mixing ratio comes from the prescribed early morning CO2 mixing ratios in the stable boundary layer, and in the free atmosphere. Errors in these values influence CO2 mixing ratios inversely proportional to the boundary layer depth (h), just like uncertainties in the assumed initial boundary layer depth and surface CO2 flux. The influence of uncertainties in the boundary layer depth itself are one order of magnitude smaller. If we "invert" the problem and calculate CO2 surface exchange from observed or simulated CO2 mixing ratios, the sensitivities to errors in boundary layer dynamics also invert: they become linearly proportional to the boundary layer depth. We demonstrate these relations for a typical well characterized situation at the Cabauw tower in the Netherlands, and conclude that knowledge of the temperature and carbon dioxide vertical profiles in the early morning are of vital importance to correctly interpret observed CO2 mixing ratios during midday. [ABSTRACT FROM AUTHOR]

Using a Large-Eddy Simulation model, we have systematically studied the inability of boundary layer turbulence to efficiently mix reactive species. This creates regions where the species are accumulated in a correlated or anti-correlated way, thereby modifying the mean reactivity. We quantify this modification by the intensity of segregation, IS, and analyse the driving mechanisms: heterogeneity of the surface moisture and heat fluxes, various background wind patterns and non-uniform isoprene emissions. The heterogeneous surface conditions are characterized by cool and wet forested patches with high isoprene emissions, alternated with warm and dry patches that represents pasture with relatively low isoprene emissions. For typical conditions in the Amazon rain forest, applying homogeneous surface forcings and in the absence of free tropospheric NOx, the isoprene-OH reaction rate is altered by less than 10 %. This is substantially smaller than the previously assumed IS of 50% in recent large-scale model analyses of tropical rain forest chemistry. Spatial heterogeneous surface emissions enhance the segregation of species, leading to alterations of the chemical reaction rates up to 20 %. The intensities of segregation are enhanced when the background wind direction is parallel to the borders between the patches and reduced in the case of a perpendicular wind direction. The effects of segregation on trace gas concentrations vary per species. For the highly reactive OH, the differences in concentration averaged over the boundary layer are less than 2% compared to homogeneous surface conditions, while the isoprene concentration is increased by as much as 12% due to the reduced chemical reaction rates. These processes take place at the sub-grid scale of chemistry transport models and therefore need to be parameterized. [ABSTRACT FROM AUTHOR]

The article describes the physical and numerical formulation of Dutch Atmospheric Large-Eddy Simulation (DALES) 3.2 version and offers insights on its applications and accomplishments. It claims that DALES is a large-eddy simulation code for studies of the physics of the atmospheric boundary layer (ABL) and of more specific cases such as dispersion and of turbulent reacting flows in the ABL. It adds an outlook on future studies that are planned to be done with DALES and on future improvements.

The article discusses the extensive description of the physical and numerical formulation of the Dutch Atmospheric Large-Eddy Simulation (DALES). The model can be applied to studies including atmospheric boundary layer, flow over sloping or heterogeneous terrain, and dispersion of inert and chemically active species. The resolution of turbulent scales larger than a certain filter width and the parameterization of smaller, less energetic scales are aimed in Large-Eddy Simulations (LES).